ML-For-Beginners/2-Regression/4-Logistic

Logistic Regression to Predict Categories

Sketchnote on Logistic Regression

Pre-lecture quiz

Introduction

In this final lesson on Regression, one of the basic 'classic' ML techniques, we will take a look at Logistic Regression. You would use this technique to discover patterns to predict categories.

In this lesson, you will learn:

• A new library for data visualization
• Techniques for Logistic Regression

Prerequisite

Having worked with the pumpkin data, we are now familiar enough with it to realize that there's one small category that we can work with: Color. Let's build a Logistic Regression model to predict that, given a pumpkin's size, what color it will be (orange or white). There is also a 'striped' category in our dataset but there are few instances, so we will not use it.

🎃 Fun fact, we sometimes call white pumpkins 'ghost' pumpkins. They aren't very easy to carve, so they aren't as popular as the orange ones but they are cool looking!

Preparation

We have loaded up the starter notebook with pumpkin data once again and cleaned it so as to preserve a dataset containing Color and Item Size.

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🚀Challenge

Add a challenge for students to work on collaboratively in class to enhance the project

Optional: add a screenshot of the completed lesson's UI if appropriate

Post-lecture quiz

Review & Self Study

Assignment: Assignment Name